{"id":"https://openalex.org/W4385697715","doi":"https://doi.org/10.3390/rs15163936","title":"Joint Posterior Probability Active Learning for Hyperspectral Image Classification","display_name":"Joint Posterior Probability Active Learning for Hyperspectral Image Classification","publication_year":2023,"publication_date":"2023-08-09","ids":{"openalex":"https://openalex.org/W4385697715","doi":"https://doi.org/10.3390/rs15163936"},"language":"en","primary_location":{"id":"doi:10.3390/rs15163936","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15163936","pdf_url":"https://www.mdpi.com/2072-4292/15/16/3936/pdf?version=1691551252","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/15/16/3936/pdf?version=1691551252","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100607415","display_name":"Shuying Li","orcid":"https://orcid.org/0000-0003-3994-2874"},"institutions":[{"id":"https://openalex.org/I4391012619","display_name":"Shanghai Artificial Intelligence Laboratory","ror":"https://ror.org/03wkvpx79","country_code":null,"type":"facility","lineage":["https://openalex.org/I4391012619"]},{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuying Li","raw_affiliation_strings":["School of Automation, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an 710121, China","Shanghai Artificial Intelligence Laboratory, Shanghai 200232, China"],"affiliations":[{"raw_affiliation_string":"School of Automation, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an 710121, China","institution_ids":["https://openalex.org/I4210136859"]},{"raw_affiliation_string":"Shanghai Artificial Intelligence Laboratory, Shanghai 200232, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4391012619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100664829","display_name":"Shaowei Wang","orcid":"https://orcid.org/0000-0003-0143-556X"},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaowei Wang","raw_affiliation_strings":["School of Automation, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an 710121, China"],"affiliations":[{"raw_affiliation_string":"School of Automation, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an 710121, China","institution_ids":["https://openalex.org/I4210136859"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100429992","display_name":"Qiang Li","orcid":"https://orcid.org/0000-0002-6736-3389"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qiang Li","raw_affiliation_strings":["School of Electronic Engineering, Xidian University, Xi\u2019an 710071, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic Engineering, Xidian University, Xi\u2019an 710071, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100429992"],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":0.1576,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.49420977,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"15","issue":"16","first_page":"3936","last_page":"3936"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9930999875068665,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9930999875068665,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9916999936103821,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9611999988555908,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.7217380404472351},{"id":"https://openalex.org/keywords/posterior-probability","display_name":"Posterior probability","score":0.6898741126060486},{"id":"https://openalex.org/keywords/joint-probability-distribution","display_name":"Joint probability distribution","score":0.6041038036346436},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5893773436546326},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5761032700538635},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5662766695022583},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5305386185646057},{"id":"https://openalex.org/keywords/conditional-random-field","display_name":"Conditional random field","score":0.5258679389953613},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.4693746566772461},{"id":"https://openalex.org/keywords/conditional-probability","display_name":"Conditional probability","score":0.453675240278244},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41611942648887634},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2573873996734619},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.2248062789440155},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.19393780827522278},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.16671288013458252}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7217380404472351},{"id":"https://openalex.org/C57830394","wikidata":"https://www.wikidata.org/wiki/Q278079","display_name":"Posterior probability","level":3,"score":0.6898741126060486},{"id":"https://openalex.org/C18653775","wikidata":"https://www.wikidata.org/wiki/Q1333358","display_name":"Joint probability distribution","level":2,"score":0.6041038036346436},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5893773436546326},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5761032700538635},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5662766695022583},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5305386185646057},{"id":"https://openalex.org/C152565575","wikidata":"https://www.wikidata.org/wiki/Q1124538","display_name":"Conditional random field","level":2,"score":0.5258679389953613},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.4693746566772461},{"id":"https://openalex.org/C44492722","wikidata":"https://www.wikidata.org/wiki/Q327069","display_name":"Conditional probability","level":2,"score":0.453675240278244},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41611942648887634},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2573873996734619},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.2248062789440155},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.19393780827522278},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.16671288013458252},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs15163936","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15163936","pdf_url":"https://www.mdpi.com/2072-4292/15/16/3936/pdf?version=1691551252","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:41f6432563c84387830fdb3ce6d17aee","is_oa":true,"landing_page_url":"https://doaj.org/article/41f6432563c84387830fdb3ce6d17aee","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 15, Iss 16, p 3936 (2023)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/15/16/3936/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs15163936","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing; Volume 15; Issue 16; Pages: 3936","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs15163936","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15163936","pdf_url":"https://www.mdpi.com/2072-4292/15/16/3936/pdf?version=1691551252","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.4099999964237213}],"awards":[{"id":"https://openalex.org/G6733412380","display_name":null,"funder_award_id":"2022ZD0160401","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4385697715.pdf"},"referenced_works_count":28,"referenced_works":["https://openalex.org/W1528789833","https://openalex.org/W1972814520","https://openalex.org/W1988747891","https://openalex.org/W2016860790","https://openalex.org/W2025263547","https://openalex.org/W2034644270","https://openalex.org/W2062432961","https://openalex.org/W2098758111","https://openalex.org/W2101365302","https://openalex.org/W2107131609","https://openalex.org/W2150045166","https://openalex.org/W2166229804","https://openalex.org/W2341894713","https://openalex.org/W2614326984","https://openalex.org/W2762884213","https://openalex.org/W2989697276","https://openalex.org/W2996636458","https://openalex.org/W3005983949","https://openalex.org/W3185173125","https://openalex.org/W4250800088","https://openalex.org/W4283008467","https://openalex.org/W4294310997","https://openalex.org/W4309158361","https://openalex.org/W6631412525","https://openalex.org/W6637241018","https://openalex.org/W6799140174","https://openalex.org/W6838988107","https://openalex.org/W6842960539"],"related_works":["https://openalex.org/W2166748330","https://openalex.org/W4252552567","https://openalex.org/W2396130432","https://openalex.org/W2885051393","https://openalex.org/W1539131693","https://openalex.org/W4220678766","https://openalex.org/W4302438394","https://openalex.org/W2953386691","https://openalex.org/W2159199674","https://openalex.org/W1578411263"],"abstract_inverted_index":{"Active":[0],"learning":[1,73],"(AL)":[2],"is":[3,51,90,110,128],"an":[4,66],"approach":[5,127],"that":[6],"can":[7],"reduce":[8],"the":[9,12,25,30,35,39,42,81,95,98,105,114,132,137,142,152],"dependence":[10],"on":[11,146],"labeled":[13],"set":[14],"significantly.":[15],"However,":[16],"most":[17],"current":[18],"active-learning":[19,67,82],"methods":[20],"are":[21],"only":[22],"concerned":[23],"with":[24,75],"first":[26,43],"two":[27,147],"columns":[28],"of":[29,48,136,154],"posterior":[31,46,70,99],"probability":[32,100],"matrix":[33],"during":[34],"sampling":[36,83,87],"phase.":[37],"When":[38],"difference":[40],"between":[41,107],"and":[44,140],"second-largest":[45],"probabilities":[47],"several":[49],"samples":[50,109,116],"proximate,":[52],"these":[53,62],"approaches":[54],"fail":[55],"to":[56,130],"distinguish":[57],"them":[58],"further.":[59],"To":[60],"improve":[61],"deficiencies,":[63],"we":[64],"propose":[65],"algorithm,":[68],"joint":[69],"probabilistic":[71],"active":[72],"combined":[74],"conditional":[76,123],"random":[77,124],"field":[78,125],"(JPPAL_CRF).":[79],"In":[80],"phase,":[84],"a":[85,122],"new":[86],"decision":[88],"function":[89],"built":[91],"by":[92],"jointing":[93],"all":[94],"information":[96,135],"in":[97],"matrix.":[101],"By":[102],"doing":[103],"so,":[104],"variability":[106],"different":[108],"refined,":[111],"which":[112],"makes":[113],"selected":[115],"more":[117],"meaningful":[118],"for":[119],"classification.":[120],"Then,":[121],"(CRF)":[126],"applied":[129],"mine":[131],"regional":[133],"spatial":[134],"hyperspectral":[138,149],"image":[139],"optimize":[141],"classification":[143],"results.":[144],"Experiments":[145],"common":[148],"datasets":[150],"validate":[151],"effectiveness":[153],"JPPAL_CRF.":[155]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
